An interventional study of WGS and RNA sequencing and circulating tumor DNA (ctDNA) in High Grade Ovarian Serous Adenocarcinoma and High Grade Serous Carcinoma, sponsored by Turku University Hospital. Recruiting at 1 site in Finland. Open to female participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-01-16.
Sponsored by Turku University Hospital · Not applicable, Interventional, and Basic science
Chemotherapy resistance is the greatest contributor to mortality in advanced cancers and severe challenges remain in finding effective treatment modalities to cancer patients with metastasized and relapsed disease. High-grade serous ovarian cancer (HGSOC) is typically diagnosed at a stage where the disease is already widely spread to the abdomen and current standard of practice treatment consists of surgery followed by platinum-taxane based chemotherapy and maintenance therapy. While 90% of HGSOC patients show no clinically detectable signs of cancer after surgery and chemotherapy, only 43% of the patients are alive five years after diagnosis because of chemoresistant cancer.
This prospective, observational trial focuses on revealing major mechanisms causing chemoresistance in HGSOG patients and derive personalized treatment regimens for chemotherapy resistant HGSOC patients. The investigators recruit newly diagnosed advanced stage HGSOC patients who are then thoroughly followed during their cancer treatment. Longitudinal sampling includes digitalized H\&E stained histology slides mainly collected during routine diagnostics, fresh tumor \& ascites samples for next-generation sequencing/proteomics (WGS, RNA-seq, DNA-methylation, ATAC-seq, ChIP-seq, mass cytometry, etc.) and ex vivo experiments, plasma samples for circulating tumor DNA (ctDNA) analyses. Broad range of clinical parameters such as laboratory and radiologic parameters (e.g., FDG PET/CT), given cancer treatments and their outcomes are collected. Radiomic analyses are performed to PET/CT and CT scans. Long-term patient derived organoid lines are established from fresh tumor tissues. Actionable genomic alterations are searched.
The general objective is to establish a clinically useful precision oncology approach based on multi-level data collected in longitudinal setting, and translate the most potent and validated discoveries into clinical use. DECIDER project will produce AI-powered diagnostic tools, cutting-edge software platforms for clinical decision-making, novel data analysis \& integration methods, and high-throughput ex vivo drug screening approaches.
Specific aims include:
Exclusion Criteria:
Diagnostic laparoscopy followed with 3-4 cycles of platinum-taxane NACT and interval debulking surgery (IDS). Treatment response is monitored with FDG PET/CT. IDS is followed by standard adjuvant therapy (ESGO/ESMO + local guidelines). Digital H\&E slides and WGS, RNAseq are obtained from performed surgeries including relapse operations/ascites drainages. Patients are followed with longitudinal ctDNA sampling.
Genetic: WGS and RNA sequencing · Genetic: circulating tumor DNA (ctDNA) · Diagnostic Test: FDG PET/CT imaging
PDS is followed by standard adjuvant therapy (ESGO/ESMO + local guidelines). Digital H\&E slides and WGS, RNAseq obtained from PDS and possible relapse operations/ascites drainages when performed. Patients are followed with longitudinal ctDNA sampling.
Genetic: WGS and RNA sequencing · Genetic: circulating tumor DNA (ctDNA) · Diagnostic Test: FDG PET/CT imaging
Successful clinical translation
The magnitude of successful clinical translation is measured by the number of times project-derived personalized medicine has impacted patients care by application of novel and existing biomarkers and therapies.
Time frame: 5 years
Successful prediction of patient outcome with AI methods
Proportion of patients whose disease outcome (PFS, OS) is predicted correctly with digital histopathology images, genomic data and routine laboratory values
Time frame: 5 years
Successful validation of potentially druggable genetic alterations
Number of potentially druggable genetic alterations found and validated with in-vitro methods
Time frame: 5 years
Successful prediction of genomic features from tumor histology
Number of genomic features that can be successfully recognized from tumor histology
Time frame: 5 years
Prediction of primary treatment response from tumor histology using H&E stained whole slide images and AI-based methods
Number of patients whose outcome (primary therapy outcome, PFS) is predicted correctly
Time frame: 5 years
Establishment of an updated version of Chemoresponse score (CRS) for measuring histological effect in tumor tissue after chemotherapy
Predictive power of the updated CRS at interval surgery is compared with traditional CRS
Time frame: 5 years
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Turku University Hospital